MétaCan
Menu
Back to cohort

The Diagnosis of Tuberculosis in Dialysis Patients

2012· review· en· W2170213658 on OpenAlexaff
Robert Richardson

Bibliographic record

VenueSeminars in Dialysis · 2012
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineTuberculosisDialysisLatent tuberculosisTuberculinHemodialysisIntensive care medicinePopulationPediatricsImmunologyInternal medicineSurgeryPathologyMycobacterium tuberculosis

Abstract

fetched live from OpenAlex

Tuberculosis is an important issue for nephrologists caring for dialysis patients. Because dialysis patients are immunocompromised, they are at higher risk for reactivation of latent tuberculosis, and they frequently have atypical presentation. Furthermore, hemodialysis units may foster rapid spread of active pulmonary tuberculosis. The diagnosis of active pulmonary tuberculosis still depends on detection of organisms by smear and culture. Newer nucleic acid detection techniques are more sensitive and specific. Nephrologists should remember that nonspecific presentation of tuberculosis including fever, weight loss, and adenopathy are more common in dialysis patients than in the general population, and diagnosis may require biopsy of extrapulmonary tissue. Detection of latent tuberculosis in dialysis patients should only be undertaken if treatment is planned. Generally, this should apply only to potential transplant candidates and younger dialysis patients with longer life expectancy. Tuberculin skin test is very insensitive in dialysis patients, and false-positives occur in patients born in countries where Bacillus Calmette-Guérin vaccine has been used. Blood tests using stimulation of gamma interferon have been shown to be more sensitive tests of latent tuberculosis and may be used in conjunction with tuberculin skin tests.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.374
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueSeminars in DialysisSame topicTuberculosis Research and EpidemiologyFrench-language works237,207